Multiobjective Multistatic Sonar Sensor Placement

Ngatchou, P.N.; Fox, Warren L. J.; El-Sharkawi, M.A.

doi:10.1109/cec.2006.1688648

Cited by 13 publications

(11 citation statements)

References 9 publications

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“…Like the Solution Approach/Methodology classification, the total number of the literature under the Research contribution category does not tally to the total number (136) of literature Of the total number of literature reviewed, only 38 papers (about 28 %) are related to the Sensor placement problem, SPP (either nodal or network placements), a widely studied problem in Optimization theory. Some of these works surveyed include (Ghafoori and Altiok, 2012;Stolkin and Florescu, 2007;Akkaya and Newell, 2009;Ibrahim et al, 2010;Ngatchou et al, 2006;Molyboha and Zabarankin, 2012), etc. Similar to the terrestrial/ generic sensor placement problem, the SPP is often addressed and solved as a coverage problem, with specific underwater environments taken into consideration.…”

Section: Research Contributionsmentioning

confidence: 99%

Literature Survey on Underwater Threat Detection

Biobaku

Lim

Cho

et al. 2015

ToMS

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This paper presents a concise review on extant literature in threat detection within the maritime domain with specific emphasis on solution methodologies, sensing technologies, regional affiliations of authors and research contributions related to underwater threat detection. The review attempts to provide an introductory framework on threat detection and surveillance within the maritime domain as opposed to its widely studied terrestrial counterpart. In all, over 200 engineering/science journal papers and conference proceedings were identified. Of these, a total of 136 articles are eventually chosen and reviewed. The analysis of this review suggests that opportunities abound in the research area, especially in Operations Research/ Management Science. Specifically, Sensor placement and deployment for underwater threat detection is identified as a significant sub-research area worth studying.

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Section: Research Contributionsmentioning

confidence: 99%

Literature Survey on Underwater Threat Detection

Biobaku

Lim

Cho

et al. 2015

ToMS

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“…Algorithms that take into account sonar performance prediction in order to design optimal multistatic active sonar fields are in development [12,13]. These methods are based on recent developments in the field of computational intelligence, and present flexible methods for solving large-dimensional optimization problems.…”

Section: Sensor Coveragementioning

confidence: 99%

“…The methodology of [13] could be extended to incorporate communications networking into the optimization algorithm. One option would be to decide on a fixed system configuration (numbers of sources and receivers), and trade off system coverage vs. system lifetime (through power usage for acoustic communications).…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Wide area ocean networks

Roy

Arabshahi

Rouseff

et al. 2006

Proceedings of the 1st ACM International Workshop on Underwater Networks - WUWNet '06

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Wide area ocean networks for monitoring and scientific exploratory purposes are in various stages of design; smallscale networks are already in various stages of deployment and testing. Clearly, cost-effective coverage is a primary underlying principle; arguably, such networks must therefore employ low-cost, energy-efficient mobile nodes. The first objective of this work is to broadly describe the architecture and system design considerations of such widearea networks with mobile nodes; secondly, we introduce the APL/UW Seaglider capabilities and provide energy estimates for propulsion and data communications. We also discuss tradeoffs, and applications in ocean coverage, and optimization of sensor coverage within constraints of a power-efficient network.

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“…After deploying the receivers, in general, we do not have any control over their positions, rather we can only decide whether or not to use those receivers at a particular time step. Transmitters can also be deployed at desired locations, and then used according to tracking requirements [3][7] [9]. However, we can improve the tracking performance further by moving the transmitters, if possible.…”

Section: Introductionmentioning

confidence: 99%

Joint path planning and sensor subset selection for multistatic sensor networks

2008

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Due to the availability of cheap passive sensors, it is possible to deploy a large number of them for tracking purposes in anti-submarine warfare (ASW). However, modern submarines are quiet and difficult to track with passive sensors alone. Multistatic sensor networks, which have few transmitters (e.g., dipping sonars) in addition to passive receivers, have the potential to improve the tracking performance. We can improve the performance further by moving the transmitters according to existing target states and any possible new targets. Even though a large number of passive sensors are available, due to frequency, processing power and other physical limitations, only a few of them can be used at any one time. Then the problems are to decide the path of the transmitters and select a subset from the available passive sensors in order to optimize tracking performance. In this paper, the PCRLB, which gives a lower bound on estimation uncertainty, is used as the performance measure. We present an algorithm to decide jointly the optimal path of the movable transmitters, by considering their operational constraints, and the optimal subset of passive sensors that should be used at each time steps for tracking multiple, possibly time-varying, number of targets. Finding the optimal solution in real time is difficult for large scale problems, and we propose a genetic algorithm based suboptimal solution technique. Simulation results illustrating the performance of the proposed algorithm are also presented.

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Multiobjective Multistatic Sonar Sensor Placement

Cited by 13 publications

References 9 publications

Literature Survey on Underwater Threat Detection

Literature Survey on Underwater Threat Detection

Wide area ocean networks

Joint path planning and sensor subset selection for multistatic sensor networks

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